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Record W2919953679 · doi:10.5539/ass.v15n3p27

Factors influencing Individual Investor Behaviour: Evidence from the Kuwait Stock Exchange

2019· article· en· W2919953679 on OpenAlexvenueno aff
Sadeq J. Abul

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsOverconfidence effectOptimismStock exchangePessimismPsychologySample (material)Herd behaviorSocial psychologyEconomicsFinanceHerding

Abstract

fetched live from OpenAlex

This study investigates the effects of psychological factors on investor behaviour regarding the Kuwait Stock Exchange (KSE). These psychological factors are, namely: excessive optimism vs pessimism, herd behaviour and risk appetite. The data for this study obtained from KSE and a survey of a random sample of 398 individual investors. By using qualitative analysis and based on the theory of behavioural finance, the study findings show that herd behaviour, optimism and psychology risk have an impact on the individual investors’ decisions. However, we did not find any evidence of overconfidence behaviour’s effects on investors’ decisions. To our knowledge, KSE has been examined by several researchers without taking into consideration the effects of psychological factors on individual investor decisions. This study finds that psychological factors play a significant role in individual investors’ decisions regarding KSE. This study might contribute positively to the development of this field of research in (KSE).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.087
GPT teacher head0.260
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2019
Admission routes1
Has abstractyes

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